class_docstr: Coreference neural model
code: def __init__(self, model_path):
      weights, biases = [], []
      for file in sorted(os.listdir(model_path)):
          if file.startswith("single_mention_weights"):
              w = np.load(os.path.join(model_path, file))
              weights.append(w)
          if file.startswith("single_mention_bias"):
              w = np.load(os.path.join(model_path, file))
              biases.append(w)
      self.single_mention_model = list(zip(weights, biases))
      weights, biases = [], []
      for file in sorted(os.listdir(model_path)):
          if file.startswith("pair_mentions_weights"):
              w = np.load(os.path.join(model_path, file))
              weights.append(w)
          if file.startswith("pair_mentions_bias"):
              w = np.load(os.path.join(model_path, file))
              biases.append(w)
      self.pair_mentions_model = list(zip(weights, biases))
  
imports: import os
  import spacy
  import numpy
  from neuralcoref.train.utils import PACKAGE_DIRECTORY, SIZE_SINGLE_IN
  from neuralcoref.train.compat import unicode_
  from neuralcoref.train.document import Document, MENTION_TYPE, NO_COREF_LIST
label_desc: Use image node_id 1 to create a new Model object from inherited base classes: object with example: obj = Model(model_path)